<!--
  speedy-vision.js
  GPU-accelerated Computer Vision for JavaScript
  Copyright 2020-2024 Alexandre Martins <alemartf(at)gmail.com>

  Licensed under the Apache License, Version 2.0 (the "License");
  you may not use this file except in compliance with the License.
  You may obtain a copy of the License at
  
      http://www.apache.org/licenses/LICENSE-2.0

  Unless required by applicable law or agreed to in writing, software
  distributed under the License is distributed on an "AS IS" BASIS,
  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  See the License for the specific language governing permissions and
  limitations under the License.

  greyscale-image.html
  Convert an image to greyscale
-->
<!doctype html>
<html>
    <head>
        <meta charset="utf-8">
        <meta name="description" content="speedy-vision.js: GPU-accelerated Computer Vision for JavaScript">
        <meta name="author" content="Alexandre Martins">
        <title>Convert image to greyscale</title>
        <link href="demo-base.css" rel="stylesheet">
        <script src="demo-base.js"></script>
        <script src="../dist/speedy-vision.js"></script>
    </head>
    <body>
        <h1>Convert image to greyscale</h1>
        <img id="image" src="../assets/speedy-wall.jpg" title="Image by Bride of Frankenstein (CC-BY)">
        <canvas id="canvas-demo"></canvas>
        <script>
window.onload = async function()
{
    /*

    This is our pipeline:

    Image  ---> Convert to ---> Image
    Source      greyscale       Sink

    */

    // Load an image
    const img = document.getElementById('image');
    const media = await Speedy.load(img);

    // Setup the pipeline
    const pipeline = Speedy.Pipeline(); // create the pipeline and the nodes
    const source = Speedy.Image.Source();
    const sink = Speedy.Image.Sink();
    const greyscale = Speedy.Filter.Greyscale();

    source.media = media; // set the media source

    source.output().connectTo(greyscale.input()); // connect the nodes
    greyscale.output().connectTo(sink.input());

    pipeline.init(source, sink, greyscale); // add the nodes to the pipeline

    // Run the pipeline
    const { image } = await pipeline.run(); // image is a SpeedyMedia

    // Display the result
    const canvas = setupCanvas('canvas-demo', image.width, image.height, img.title);
    renderMedia(image, canvas);
}
        </script>
        <section id="speedy-vision">
            <span>Powered by <a href="https://github.com/alemart/speedy-vision" target="_blank">speedy-vision.js</a></span>
            <a href="https://github.com/sponsors/alemart" target="_blank" class="button">
                <img alt="GitHub Sponsors" src="https://img.shields.io/github/sponsors/alemart?style=for-the-badge&logo=github&label=Sponsor&labelColor=royalblue&color=gold">
            </a>
        </section>
    </body>
</html>